Managing Kubernetes with AI Agents equips operations professionals to use AI-powered agents for Kubernetes management, in one intensive, hands-on day. The course opens with an introduction to Kubernetes operations agents, covering the architecture and lifecycle of tools such as k8sGPT and kagent. It then moves into using agents to auto-discover misconfigurations, generate and lint YAML, and detect and correct drift. Attendees also learn how agents support security scanning, policy validation, and RBAC audits, and see how agents can generate and validate application manifests against best practices.
Each module combines short lectures with live demonstrations and real-world lab exercises. The opening module frames agentic tooling within the broader shift toward AI in DevOps, then walks through how tools like k8sGPT and kagent are deployed inside a cluster. Configuration-focused labs have attendees auto-tune resource requests and limits alongside linting and drift-correction work, so agents handle both catching mistakes and right-sizing workloads. Security labs go beyond scanning and RBAC audits to integrate agent output with existing security tooling, giving teams a single place to review findings. Attendees leave with practical skills for deploying and directing intelligent agents against a running cluster.
Who Should Attend
DevOps, DevSecOps, Ops, SRE and other technical personnel
What Attendees Will Learn
Upon completion of the Managing Kubernetes with AI Agents course attendees will be able to:
- Deploy intelligent Kubernetes agents
- Use agents to identify workload problems
- Integrate agents with observability and other tools
- Use agents to evaluate Kubernetes security posture
- Use agents to identify Kubernetes configuration problems
- Use agents to identify gaps in Kubernetes best practices
- Use agents to generate yaml files for various configuration and management tasks
Prerequisites
Students should complete the RX-M “Kubernetes Foundation” course or have equivalent knowledge.